Junming Jian

发表

Can peritumoral radiomics increase the efficiency of the prediction for lymph node metastasis in clinical stage T1 lung adenocarcinoma on CT?

Yuguo Tang, Xiang Wang, Xingyu Zhao, 2019, European Radiology.

MR image-based radiomics to differentiate type Ι and type ΙΙ epithelial ovarian cancers

P. Pickhardt, Xingyu Zhao, W. Xia, 2020, European Radiology.

Multiple instance convolutional neural network with modality-based attention and contextual multi-instance learning pooling layer for effective differentiation between borderline and malignant epithelial ovarian tumors

Xiaodong Wu, Xingyu Zhao, Junming Jian, 2021, Artif. Intell. Medicine.

MRI Texture Analysis for Preoperative Prediction of Lymph Node Metastasis in Patients with Nonsquamous Cell Cervical Carcinoma.

Jing Zhang, Junming Jian, Yan Wei, 2022, Academic radiology.

Preoperative CECT-based Radiomic Signature for Predicting the Response of Transarterial Chemoembolization (TACE) Therapy in Hepatocellular Carcinoma

Xingyu Zhao, W. Xia, Junming Jian, 2022, CardioVascular and Interventional Radiology.

Quantitative Assessment of Tumor-Infiltrating Lymphocytes Using Machine Learning Predicts Survival in Muscle-Invasive Bladder Cancer

L. Wang, Zhiyuan Chen, Xiuheng Liu, 2022, Journal of clinical medicine.

Deep Learning Predicts Overall Survival of Patients With Unresectable Hepatocellular Carcinoma Treated by Transarterial Chemoembolization Plus Sorafenib

Rui Zhang, S. Zhang, Xingyu Zhao, 2020, Frontiers in Oncology.

Deep learning–based fully automated detection and segmentation of lymph nodes on multiparametric-mri for rectal cancer: A multicentre study

Xin Gao, Yuguo Tang, Mengmeng Wang, 2020, EBioMedicine.

MRI‐Based Multiple Instance Convolutional Neural Network for Increased Accuracy in the Differentiation of Borderline and Malignant Epithelial Ovarian Tumors

Xingyu Zhao, W. Xia, Junming Jian, 2021, Journal of magnetic resonance imaging : JMRI.

CT-based radiomics signatures can predict the tumor response of non-small cell lung cancer patients treated with first-line chemotherapy and targeted therapy

S. Yuan, Xingyu Zhao, W. Xia, 2021, European Radiology.

Fully convolutional networks (FCNs)-based segmentation method for colorectal tumors on T2-weighted magnetic resonance images

Xin Gao, Rui Zhang, Xiaodong Wu, 2018, Australasian Physical & Engineering Sciences in Medicine.

A cross-modal 3D deep learning for accurate lymph node metastasis prediction in clinical stage T1 lung adenocarcinoma.

Yuguo Tang, Xiang Wang, Xingyu Zhao, 2020, Lung cancer.

Contribution of whole slide imaging‐based deep learning in the assessment of intraoperative and postoperative sections in neuropathology

Liang Shen, Liting Shi, W. Xia, 2023, Brain pathology.

Deep learning-based segmentation of epithelial ovarian cancer on T2-weighted magnetic resonance images

Junming Jian, Yong'ai Li, Xin Gao, 2023, Quantitative imaging in medicine and surgery.

Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma: Initial Application of a Radiomic Algorithm Based on Grayscale Ultrasound Images

Xingyu Zhao, W. Xia, Junming Jian, 2020, Frontiers in Oncology.

Deep Learning Predicts Overall Survival of Patients with Unresectable Hepatocellular Carcinoma Treated by Transarterial Chemoembolization Plus Sorafenib: A Multicenter Study

Xingyu Zhao, W. Xia, Junming Jian, 2020, SSRN Electronic Journal.

Fully convolutional networks (FCNs)-based segmentation method for colorectal tumors on T2-weighted magnetic resonance images

W. Xia, Junming Jian, Xin Gao, 2018, Australasian Physical & Engineering Sciences in Medicine.

MRI-Based Machine Learning for Differentiating Borderline From Malignant Epithelial Ovarian Tumors: A Multicenter Study.

P. Pickhardt, Xingyu Zhao, W. Xia, 2020, Journal of magnetic resonance imaging : JMRI.

Deep Learning-Based Fully Automated Segmentation of Regional Muscle Volume and Spatial Intermuscular Fat Using CT.

W. Xia, Junming Jian, Xin Gao, 2023, Academic radiology.

Full convolutional network based multiple side-output fusion architecture for the segmentation of rectal tumors in magnetic resonance images: A multi-vendor study.

Xin Gao, Mengmeng Wang, Zhao Ran, 2019, Medical physics.

3D multi-scale, multi-task, and multi-label deep learning for prediction of lymph node metastasis in T1 lung adenocarcinoma patients' CT images

Yuguo Tang, Xiang Wang, Xingyu Zhao, 2021, Comput. Medical Imaging Graph..

Deep learning-based fully automated diagnosis of melanocytic lesions by using whole slide images

Xingyu Zhao, Junming Jian, Xin Gao, 2022, The Journal of dermatological treatment.

Peritumoral MRI Radiomics Features Increase the Evaluation Efficiency for Response to Chemotherapy in Patients With Epithelial Ovarian Cancer.

Junming Jian, Yong'ai Li, J. Qiang, 2024, Journal of magnetic resonance imaging : JMRI.